人工智能和大数据分析技术在热连轧辊道电机故障分析中的应用  

Application of Artificial Intelligence and Big Data Analysis Technologies in Fault Analysis of Hot Rolling Mill Motor

作　　者：刘恒文 刘昱轩 赵庆浩 LIU Hengwen;LIU Yuxuan;ZHAO Qinghao(National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing,University of Science and Technology Beijing,Beijing 100083,China)

机构地区：[1]北京科技大学高效轧制与智能制造国家工程中心,北京100083

出　　处：《自动化应用》2024年第7期1-3,共3页Automation Application

基　　金：国家自然科学基金(52004029)。

摘　　要：通过研究并应用人工智能和大数据分析技术,提高热连轧辊道电机故障分析的效率和准确性。通过对热连轧辊道电机运行情况进行分析和建模,探索一条准确有效的电机异常诊断建模路线,并引入大数据分析技术,利用大数据处理平台和相关算法,进一步提高诊断的精确性,使现场技术人员在电机运转过程能够及时发现潜在的故障问题,从而提高生产效率。By studying and applying artificial intelligence and big data analysis technologies,it aims to enhance the efficiency and accuracy of fault analysis in hot rolling mill motors.Through the analysis and modeling of the operation of hot rolling mill motors,seek to explore a precise and effective modeling approach for motor anomaly diagnosis,and introduce big data analysis technologies,leveraging big data processing platforms and relevant algorithms to further improve the accuracy of diagnosis.This enables on-site technicians to promptly detect potential issues during motor operation,thereby increasing production efficiency.

关 键 词：人工智能 大数据分析 热连轧辊道电机 故障诊断 状态监测 

分 类 号：TG333.71[金属学及工艺—金属压力加工]